Meta-analysis of crashes on two-lane rural highways using Bayesian Networks and Random Forest

It became evident that using a hybrid meta-learning methodology based on BNs and RF was helpful in identifying the most significant factors, which influence the negative outcome of crashes. Local criteria that may evaluate the traffic safety of present and future highways should be developed and put into use in order to improve the level of traffic safety in two-lane rural highways, reducing the severity of injuries caused by traffic crashes and improving traffic safety.

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Publication Details

Journal
Traffic Injury Prevention
Published
2025-04-04
DOI
https://doi.org/10.1080/15389588.2025.2472271
Citations
2
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
2.61
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article

Meta-analysis of crashes on two-lane rural highways using Bayesian Networks and Random Forest

Randa Oqab Mujalli, Alejandro Ruiz-Padillo, Laura Garach
2 citations
Traffic Injury Prevention
Traffic and Road Safety
2.61
article

Meta-analysis of crashes on two-lane rural highways using Bayesian Networks and Random Forest

Randa Oqab Mujalli, Alejandro Ruiz-Padillo, Laura Garach
article en
2 citations

Abstract

It became evident that using a hybrid meta-learning methodology based on BNs and RF was helpful in identifying the most significant factors, which influence the negative outcome of crashes. Local criteria that may evaluate the traffic safety of present and future highways should be developed and put into use in order to improve the level of traffic safety in two-lane rural highways, reducing the severity of injuries caused by traffic crashes and improving traffic safety.

Traffic Injury PreventionVol. 26(8)
Hashemite University (JO), Universidad de Granada (ES), Universidade Federal de Santa Maria (BR)
Sustainable cities and communities
Openalex Percentile: Top 13%
Traffic and Road Safety
2.61
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